Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Preconditioned Richardson Method
Graph Chatbot
Related lectures (30)
Previous
Page 3 of 3
Next
Solving the linear system - Nonlinearity
Explores solving linear systems and addressing nonlinearity in numerical flow simulations using multigrid and linearization methods.
Newton's Method: Convergence and Criteria
Explores the Newton method for non-linear equations, discussing convergence criteria and stopping conditions.
Eigenvalues and Eigenvectors
Explores eigenvalues, eigenvectors, and methods for solving linear systems with a focus on rounding errors and preconditioning matrices.
Gradient Descent
Covers the concept of gradient descent in scalar cases, focusing on finding the minimum of a function by iteratively moving in the direction of the negative gradient.
Construction of an Iterative Method
Covers the construction of an iterative method for linear systems, emphasizing matrix decomposition and convexity.
Richardson Method: Preconditioned Iterative Solvers
Covers the Richardson method for solving linear systems with preconditioned iterative solvers and introduces the gradient method.
Construction of an Iterative Method
Covers the construction of an iterative method for linear systems by decomposing a matrix A into P, T, and P_A.
Newton Method: Data Interpolation
Covers the Newton method for finding zeros of functions using data interpolation.
Convergence Analysis: Iterative Methods
Covers the convergence analysis of iterative methods and the conditions for convergence.
Matrix Construction and Function Manipulation
Covers tips on matrix construction and function manipulation using MATLAB.
